import tensorflow as tf
import matplotlib.pyplot as plt
import numpy as np
from tensorflow import _keras

plt.rcParams['figure.dpi'] = 180
plt.rcParams['axes.grid'] = False

fashion_mnist = tf.keras.datasets.fashion_mnist
(train_images, train_labels), (test_images, test_labels) = fashion_mnist.load_data()

plt.figure(figsize=(15, 15))

for index in range(25):
    plt.subplot(5, 5, index + 1)
    plt.xticks([])
    plt.yticks([])
    image = test_images[index]
    true_label = test_labels[index]
    predict_array = predict_array[index]
    plt.imshow(image, cmap=plt.cm.binary)



plt.imshow(train_images[0])
plt.colorbar()
plt.grid(False)